All In The Algorithm

Somewhere between artistry and automation lies the algorithm, the always mysterious and sometimes magical algorithm. Like the alchemist’s dream of turning base metal into gold, a good
video search and discovery (S&D) algorithm spins raw data into RPM (revenue per thousand) treasure.

More powerful than technology and the patents that protect it
(destined to be overcome by better technology) the successful algorithm retains its allure and at least the illusion of being unassailable, as platforms, formats, and OS’s come and
go. If you want a video S&D product that is distinguished from all others and that consumers will return to again and again, you need an algorithm.

As consumers, we
want to know that:

We have attractive options.

The option we choose will probably be a good choice.

If it doesn’t work out, we still have other options.

The algorithm can help fulfill these basic wants.

A good algorithm works quickly. It analyzes data in real time and produces instant results. Finding something quickly
provides instant gratification and saves the user valuable time which can be spent enjoying a video instead of searching for one.

Unlike algorithms operating in the financial
markets where the goal is to find and execute as many targeted transactions as rapidly as possible, the goal of video S&D should be to quickly identify a reasonable number of
alternative titles with a high probability that at least one alternative will be selected by the user.

The most important attributes of the effective algorithm for video S&D
are: 1) rapid parsing of the largest number of influencing factors, each of which increase the probability that the results presented will be appropriate and a selection will be made, 2) the
order in which the options are presented (best options first) and 3) limiting the number of options presented to make it easier to choose. These attributes are more important than the raw
number of “results” served.

Current video S&D algorithms often rely too heavily on a single factor: personal behavior. Focusing relentlessly on personal behavior
can result in an unhealthy narrowing of choice for the user. What is the probability that if you watched X last, you will watch Y next, or something like it? Even if at all
predictive, past practice is not necessarily the best indicator of what I would consider the best choice for what to watch next. If I am offered a chocolate because I just ate a chocolate, I may
well take another one -- but it does not mean that I really wanted another chocolate or that I feel good about taking one. It may just as likely make me sad and depressed -- wishing that I would
stop being offered chocolates.

Other more immediately relevant influencing factors may be what other people are looking for at this moment; what my friends are watching now; what
influencers are talking about, what screen size I am watching on; where I am; what day it is, what time of day it is; etc.

An algorithm should also not stand alone. It has to
be a part of a complex of solutions to the challenge “what to watch.” A live editorial component offers a provider-differentiating POV and context for the consumer that
takes timeliness, the brand identity of the provider, human interest, and aesthetics into account: sensitivities that the automaton is blind to. Promotional considerations should be factored in:
what and where are the deals? Goal orientation is important: I want to search for and introduce myself to "Dr. Who." Where and how should I start? Which Dr.? Which
episode? This requires input from the expert(s). But it is the algorithm that provides the core engine, anchoring the total experience. It is the failsafe that ensures
freshness and variety.

Ultimately, mystery underlies the S&D algorithm’s strength. How good the algorithm actually is may be of less immediate importance than how good everyone
believes it is. Algorithms are not open to public scrutiny. No one gets to review the elegance of its structure or lines of code in the same way you can admire and deconstruct a good
poem. It keeps its secrets. It does have to earn initial trust, but if it performs well upon first trial and is generally believed to be the best algorithm, all will submit to
its power and you will have an enduring asset. And that’s why YOUR algorithm is worth creating, having, and nurturing.